When a military asset such as an aircraft is simultaneously illuminated by multiple radar systems (threat systems), it may be useful to sort the received radar pulses into groups, or clusters, according to their source. An asset may, for example, be illuminated by several different radars from different directions, each having a different combination of amplitude, carrier frequency, pulse width, and modulation type. The received radar pulses may be detected and analyzed by a radar analysis system such as a radar warning receiver (RWR), which may then identify each source as being, for example, ship-board radar, aircraft radar, or missile radar.
Radar pulses from multiple sources may be interleaved in time when they arrive at the radar analysis system. As a first step in analyzing the received pulses it may be desirable to deinterleave them (i.e., to form multiple individual pulse trains, each corresponding to one of the radar sources as illustrated, for example, in FIG. 1). This may be particularly important for determining certain characteristics of each source: in a stream of pulses from several sources, for example, each operating at a different pulse repetition interval (PRI), it is difficult to infer the PRI of any one source without first separating (i.e., deinterleaving), the stream into separate pulse trains, one pulse train for each source (e.g., as illustrated in FIG. 1). Once the stream is deinterleaved the PRI of each source is, in the ideal case, simply the rate at which pulses occur in the corresponding pulse train. Even if some pulses are lost in processing, the PRI of a given source may be estimated from the remaining pulses, for example by inserting pulses as needed to produce a regular sequence of pulses. Other attributes such as the carrier frequency may be determined from a single pulse, but it may be possible to determine it more accurately from a series of pulses originating from the same source.
Prior art systems may perform deinterleaving by grouping received pulses into “clusters” of similar pulses. Pulses that are, according to some measure of similarity, sufficiently similar, are deemed to have originated from a single source, and pulses that are dissimilar are deemed to have originated from different sources. Various attributes, or parameters, may be compared when assessing the degree of dissimilarity, or “distance,” between pulses, including frequency, the direction from which the pulses arrived or angle of arrival (AOA), pulse width, and amplitude. A weighted measure of distance may be used. In such a measure a weight may be defined for each parameter and differences in any parameter multiplied by the corresponding weight.
Selecting the weights for a weighted distance generally involves making a compromise between the respective likelihoods of two types of error. If a weight is made too large (i.e., the distance and resulting cluster window are too small), pulses originating from the same source may be incorrectly classified as originating from different sources; if the weight is made too small (i.e., the distance and resulting cluster window are too big), pulses originating from different sources may incorrectly be classified as originating from the same source. If the measurement error in a parameter is large, it may be preferable to use a small weight, so that variations in the measured value due to measurement error do not cause pulses, which in fact are quite similar, to be classified as originating from different sources. Thus the optimum weights may vary, depending on operating conditions. At high temperature, for example, amplifier noise in the receiver may cause the measurement error for some parameters to increase, with the result that smaller weights may be preferred at higher temperatures.
In prior art deinterleavers, the weights may be static (fixed) prior to operation, and they may be independent of the pulse parameters. However, modern, more advanced radar emitters are capable of dynamically varying and randomizing signal parameters, such as for example, waveform, frequency, pulse width, and/or pulse repetition interval. When faced with such advanced radar emitter threats, traditional static weight deinterleavers will either fail to identify the threat entirely, or will misidentify the threat.